Head to head · LLM inference · October 2026 research run

Gemini 4 Carbon vs Inkling 2 Small

Gemini 4 Carbon scores 62.6 (B) on agent readiness against Inkling 2 Small's 52.1 (D), and leads in 5 of 7 scored categories. Both do llm inference.

Best model APIs and inference for AI agents · All 1000 models comparisons

Which one, for what

Gemini 4 Carbon B

Best for Agents on the hardest long tasks (multi-step debugging, large codebases, open-ended research, security work) that can pay frontier prices and already use the Gemini API.

Ahead on

  • Reliability, 40 against 30
  • Schema & documentation, 85 against 70
  • Agent ergonomics, 93 against 62
  • Maintenance & community, 83 against 75
  • Transparency & trust, 72 against 64

Watch for

Paid tier only, with no free tier to try it on

Inkling 2 Small D

Best for Developers who want a capable multimodal open-family model through an OpenAI-compatible API today, or to fine-tune it on Tinker, and who can live with a beta surface until the weights are published.

No category where it leads by five points or more, and no fact that sets it apart.

Watch for

Serverless inference and the OpenAI-compatible API are both labelled beta, with a waitlist for higher throughput

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Agent ergonomics Gemini 4 Carbon +31

Gemini 4 Carbon 93

Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Function calling, with forced calls by FunctionCallingConfig on the API (20). Structured output (13 of 15). Implicit caching with durable caching on by default, cached input 95% off, explicit caches not supported, per the Cloud guide read on 10 November (15). 1,048,576 tokens shared between input and output (15). Batch at half price on the platform (10). Python and JavaScript SDKs (10). Error codes with backoff guidance (10 of 15). 20 + 13 + 15 + 15 + 10 + 10 + 10 = 93.

Inkling 2 Small 62

Model reading (tool use, structured output, caching, context, batch, SDKs). A 256K served context, max_tokens and a priced cache at $0.03 per million; tool use isn't documented for this model (15 of 25). Output-size controls through max_tokens, reasoning_effort and separate_reasoning (15 of 20). One documented error, the 400 for unsupported reasoning_effort (5 of 20). Stable request IDs make SDK sampling retries safe, per the tinker listing (15 of 20). OpenAI's SDKs work against the endpoint, with Tinker's Python SDK besides, and reasoning defaults to 0.9 (12 of 15). 15 + 15 + 5 + 15 + 12 = 62.

Schema & documentation Gemini 4 Carbon +15

Gemini 4 Carbon 85

Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Discovery document for GenerateContent (20 of 25). llms.txt with Markdown twins (10). The Cloud developer guide says what Carbon takes and refuses, the parameters that return 400 or are ignored, and how to migrate (15 of 20). Structured output to a JSON Schema with some keywords not enforced (10 of 15). Examples and an errors page (15). Dated changelog and model versions (15). 20 + 10 + 15 + 10 + 15 + 15 = 85.

Inkling 2 Small 70

Model reading. No OpenAPI file of its own; the OpenAI-compatible chat and completions endpoints and the typed Python SDK are the contract, as the tinker listing reads it (15). llms.txt on the docs host, per the tinker listing's 1 October check (10). The model card states intended use (agentic and tool-use systems, coding assistants, chatbots, RAG), inputs, outputs and limitations, and the launch post its benchmarks (16 of 20). Model IDs, context lengths and the reasoning_effort values (none to xhigh, or 0.0 to 0.99) are documented; the tool-call format and structured output aren't, for this model (8 of 15). A Python example and an HTTP 400 for models without reasoning_effort, with no error page (6 of 15). A dated Tinker changelog and a model deprecations page, per the tinker listing (15). 15 + 10 + 16 + 8 + 6 + 15 = 70.

Reliability Gemini 4 Carbon +10

Gemini 4 Carbon 40

Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Status page at aistudio.google.com/status with no readable components or history (10 of 20) and no readable incident record (5 of 30). Rate-limit tiers and spend limits published, per-model limits in AI Studio (5 of 15). Backoff guidance for 429 and 503 and SDK retries (15). No SLA (0). Carbon's launch stage isn't stated in Google's developer post, the Antigravity post or the Cloud developer guide read on 10 November, and the model ID carries no preview label, so half (5 of 10, a judgement call; Argon's GA earned the platform 10). 10 + 5 + 5 + 15 + 0 + 5 = 40.

Inkling 2 Small 30

Model reading, for the surface it's called on, Tinker's serverless inference and OpenAI-compatible API. No status page found, per the tinker listing's checks of 1 October and 4 November (0), so no readable incident history (5). The only published limit is the in-flight sample cap of 2,000, per the tinker listing's 1 October check; the OpenAI-compatible page gives no numbers and says higher or more stable throughput needs the waitlist (10). The SDK retries sampling with stable request IDs, per the tinker listing's reading of the SDK repository; the OpenAI-compatible page has no retry guidance (15). No SLA found (0). Serverless inference is 'currently in beta' on the models and pricing page and the OpenAI-compatible API is labelled Beta, read 6 November (0). 0 + 5 + 10 + 15 + 0 + 0 = 30.

Maintenance & community Gemini 4 Carbon +8

Gemini 4 Carbon 83

Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Released to developers on 10 November 2026, with the platform's changelog (30). Deprecations with earliest dates and no stated minimum notice (4 of 12). Shutdowns in the last 90 days kept to their table (4 of 8). Dated changelog (15). SDK replies not sampled (5 of 10). Current SDKs (15). Runtimes stated (10). 30 + 4 + 4 + 15 + 5 + 15 + 10 = 83.

Inkling 2 Small 75

Model reading. Released 5 November 2026 (30). Churn and notice in place of release counts: Inkling, Inkling-Small (30 July) and Inkling 2 Small in about four months, and a deprecations page with dated retirements and a promise to 'aim to give advance notice' by email, with no stated period, per the tinker listing (10 of 20). A public changelog and a support address and Discord, per the tinker listing (10 of 15). Current official SDKs, Tinker's Python SDK and the OpenAI-compatible endpoint (15). SDK and cookbook CI, per the tinker listing (10). 30 + 10 + 10 + 15 + 10 = 75.

Transparency & trust Gemini 4 Carbon +8

Gemini 4 Carbon 72

Model reading for gemini-4-carbon on the Gemini API. Platform facts are the Gemini API listing's (gemini-api, re-read 1 November), carried over as RULES.md allows for a model on an already graded platform. Closed service with clear terms, SDKs Apache-2.0 (15). Paid-tier data isn't used, abuse retention has no number, and request storage is on by default for new paid projects (20 of 30). Deprecations table (15 of 20). Data may be cached anywhere Google has facilities; no subprocessor list checked (5 of 20). Every benchmark figure is Google's own. 15 + 20 + 15 + 5 = 55.

Inkling 2 Small 64

Editorial half. Closed for now under the Tinker Terms of Use and the Model Acceptable Use Policy, per the model card, with Apache 2.0 weights promised the week after launch (15). Terms commit not to use Customer Content for training, keep it only as needed, with a DPA and deletion on request; the privacy notice wasn't re-read, per the tinker listing (15). Dated deprecation notices with no stated period (15). The DPA annex names Google Cloud, Cloudflare, WorkOS and OpenAI with service and location (15). 15 + 15 + 15 + 15 = 60.

Score by category

CategoryWeight this runGemini 4 CarbonInkling 2 SmallEdge
Reliability16%204030Gemini 4 Carbon +10
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28570Gemini 4 Carbon +15
Agent ergonomics13%16.29362Gemini 4 Carbon +31
Security & auth14%17.55557Inkling 2 Small +2
Payments & pricing10%12.52020even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88375Gemini 4 Carbon +8
Transparency & trust7%8.87264Gemini 4 Carbon +8
Negative events≤1500
TotalB 62.6/100D 52.1/100

Facts side by side

FactGemini 4 CarbonInkling 2 Small
KindModel APIModel API
VendorGoogleThinking Machines Lab
Hosted endpointhttps://generativelanguage.googleapis.com/v1betahttps://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1
Transports
AuthAPI keyAPI key
PricingPay per usePay per use
x402nono
LicenceClosed model, used through the Gemini API and Google's apps under Google's termsProprietary for now, used through Tinker under the Tinker Terms of Use and Thinking Machines' Model Acceptable Use Policy, per the model card. Thinking Machines says it will publish the weights under Apache 2.0 the week after launch, once outside safety testing is done
Read-only variant documentednono
llms.txtyesyes
Last release2026-11-102026-11-05
Terms last updated2026-04-28not read yet
Privacy policy last updated2026-10-01not read yet
Customer content may train modelsyesnot read yet
Terms restrict automated accessyesnot read yet
Terms restrict benchmarkingyesnot read yet
Terms or service can change without noticenot found in the textnot read yet
Arbitration or class-action waivernot found in the textnot read yet

Verdicts

Gemini 4 Carbon

Google's strongest model on the same Gemini API as Argon, with a 1M-token budget, function calling and structured output, at an introductory $2 and $10 per million tokens. Paid tier only, sampling parameters are ignored or refused, its launch stage isn't stated, and the price rises to $4 and $20 at a date Google hasn't given.

Inkling 2 Small

A new multimodal mixture-of-experts model from Thinking Machines, callable today through Tinker's OpenAI-compatible endpoint at $0.30 and $1.00 per million tokens, with strong vendor-reported coding and agent scores. Tinker's serverless inference is beta, with no status page or SLA, and the weights aren't public yet.

Before you call either

Gemini 4 Carbon

  1. Call generateContent at https://generativelanguage.googleapis.com/v1beta with model gemini-4-carbon and an x-goog-api-key on a billed project
  2. Set thinking_level (LOW, MEDIUM or HIGH) instead of thinking_budget, and don't send temperature, top_p or top_k
  3. Count output against the same 1,048,576-token limit as the input, and set max_output_tokens for long answers
  4. Put static prompt content first so implicit caching applies; explicit caches aren't supported
  5. Use gemini-4-argon for most coding and knowledge work, and Carbon for the hardest long tasks, as Google suggests

Inkling 2 Small

  1. Call https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1 with an OpenAI client and TINKER_API_KEY, using /chat/completions
  2. The serverless model ID is thinkingmachines/Inkling-2-Small:peft:262144:sampling-nvfp4, per Tinker's pricing page. The OpenAI page's examples use your own checkpoint paths, so confirm it before relying on it
  3. Pass reasoning_effort as none to xhigh or 0.0 to 0.99 (default 0.9); reasoning arrives in reasoning_content unless separate_reasoning is false
  4. Keep images between 40 and 4096 px a side, per the model card
  5. Validate JSON yourself, since structured output and the tool-call format aren't documented
  6. Plan for a move to open weights. When they publish, the open-weights listing will carry sizes and runtimes

Questions

Which is better for AI agents, Gemini 4 Carbon or Inkling 2 Small?

Gemini 4 Carbon scores 62.6 (B) on agent readiness against Inkling 2 Small's 52.1 (D), and leads in 5 of 7 scored categories.

Do Gemini 4 Carbon and Inkling 2 Small need an API key?

Both need an API key.

Can an agent call Gemini 4 Carbon and Inkling 2 Small without installing anything?

Yes. Gemini 4 Carbon has a hosted endpoint at https://generativelanguage.googleapis.com/v1beta and Inkling 2 Small at https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1.

Other comparisons with Gemini 4 Carbon or Inkling 2 Small

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